evictions - Mecklenburg County - Housing & Homelessness Dashboard

CHARLOTTEMECKLENBURG

EVICTIONS

Part 2: Mapping Evictions

Released 2018 1 | CONTENTS

PREPARED FOR The Housing Advisory Board of Charlotte-Mecklenburg

FUNDING PROVIDED BY Mecklenburg County Community Support Services

PREPARED BY University of North Carolina at Charlotte Urban Institute

The Housing Advisory Board of Charlotte-Mecklenburg (HAB), formerly known as the Charlotte-Mecklenburg Coalition for Housing, is a volunteer appointed board charged with educating, advocating, engaging and partnering with community stakeholders to end and prevent homelessness and ensure a sufficient supply of affordable housing throughout the community. Members are appointed by the Mayor, City Council and the Mecklenburg Board of County Commissioners. HAB looks to national best practices and local research to make its recommendations to community stakeholders and providers, and advocates and advises on a strategic level to reduce homelessness and increase affordable housing. In addition, HAB is responsible for the governance of the Continuum of Care in Charlotte-Mecklenburg, which carries out activities as specified in 24 CFR part 578.5(b) of the Federal Register of the U.S. Department of Housing and Urban Development. The UNC Charlotte Urban Institute is a nonpartisan, applied research and community outreach center at UNC Charlotte. Founded in 1969, it provides services including technical assistance and training in operations and data management; public opinion surveys; and research and analysis around economic, environmental, and social issues affecting the Charlotte region.

CONTENTS 04

11

BACKGROUND

DATA & FINDINGS

4. Authors & Reviewers

11. Data

5. Thanks

13. Eviction Density

6. About

16. Eviction Rates and Neighborhood Clustering

7. Key Definitions 8. Introduction 9. Key Findings

23. Neighborhood Characteristics 26. Conclusion

10. Defining Evictions

27 REFERENCES & APPENDIX 27. References 28. Appendix

3 | CONTENTS

Authors & Reviewers Authors & Reviewers AUTHORS Ashley Williams Clark, MCRP

Katie Zager, MA

Justin Lane, MA

Director of Outreach & Strategic Partnerships UNC Charlotte Urban Institute

Social Research Specialist UNC Charlotte Urban Institute

Data and Research Specialist UNC Charlotte Urban Institute

With Assistance from Laura Simmons, MA Director of Community Indicators UNC Charlotte Urban Institute

REVIEWERS Dustin Elliott, Mecklenburg County Sheriff’s Office Ted Fillette, Legal Aid of North Carolina—Charlotte

Stacy Lowry, Mecklenburg County Community Support Services, Housing Advisory Board Andrey Melkonyan, Mecklenburg County Sheriff’s Office

Carol Hardison, Crisis Assistance Ministry Amy Hawn Nelson, Actionable Intelligence for Social Policy, Housing Advisory Board Helen Lipman, Mecklenburg County Community Support Services

Courtney Morton, Mecklenburg County Community Support Services Ken Szymanski, Greater Charlotte Apartment Association

ADDITIONAL INPUT PROVIDED BY City of Charlotte Community Link Crisis Assistance Ministry Greater Charlotte Apartment Association Legal Aid of North Carolina Salvation Army of Greater Charlotte

4 | Authors & Reviewers

Thanks

Thanks

FUNDING PROVIDED BY Mecklenburg County Community Support Services

MANY THANKS FOR THE ASSISTANCE OF Mecklenburg County Sheriff’s Office

Thanks | 5

About

About

The 2017 Housing Instability & Homelessness Report Series is a collection of local reports designed to better equip our community to make data-informed decisions around housing instability and homelessness. Utilizing local data and research, these reports are designed to provide informative and actionable research to providers, funders, public officials and the media as well as the general population. The Housing Advisory Board of Charlotte-Mecklenburg outlined three key reporting areas that, together, comprise the 2017 series of reports for community stakeholders. The three areas include:

1. POINT-IN-TIME COUNT An annual snapshot of the population experiencing homelessness in Mecklenburg County. This local report is similar to the national report on Point-in-Time Count numbers, and provides descriptive information about both the sheltered and unsheltered population experiencing homelessness on one night in January and the capacity of the system to shelter and house them.

2. HOUSING INSTABILITY An annual report focusing on the characteristics and impact of housing instability in the community. During the 2017 reporting cycle, this report will be divided up into several reports that focus on various aspects of evictions within Mecklenburg County.

3. SPOTLIGHT An annual focus on a trend or specific population within housing instability and homelessness. During the 2017 reporting cycle, this report will focus on the intersection of housing and schools. The 2017 reporting cycle is completed by the UNC Charlotte Urban Institute. Mecklenburg County Community Support Services provides funding for the report series. The reports can be accessed at http://MecklenburgHousingData.org

6 | About

Key Definitions Definitions Key Complaint in summary ejectment

Homeownership rate

A legal form that a landlord must complete in order to attempt to formally evict a tenant and regain possession of the premises or unit. These tenants are at risk of formal eviction.

The number of owner-occupied units as a percentage of all occupied housing units.

Cost burdened Describes when a household spends more than 30% of their gross income on rent and utilities. If a household spends more than 50% of their gross income on rent and utilities, they are considered extremely cost burdened.

Defendant In the case of complaints in summary ejectment, the defendant is the person that the plaintiff is seeking to evict.

Fair market rent According to 24 CFR 5.100, Fair Market Rent (FMR) is the rent that would be required to be paid in a particular housing market in order to obtain privately owned, decent, safe and sanitary rental housing of modest (non-luxury) nature with suitable amenities. The FMR includes utilities (except telephone). The U.S. Department of Housing and Urban Development establishes separate FMRs for dwelling units of varying sizes (number of bedrooms).

Informal eviction A process of eviction that happens outside of the court system. It could consist of a landlord telling a tenant they must move or a landlord paying a tenant to move.

Judgment in summary ejectment The small claims court magistrate or district court judge completes this legal form with their judgment in the summary ejectment case.

Plaintiff In the case of evictions, the plaintiff is typically the housing provider (also referred to as the landlord) who issues the complaint in summary ejectment.

Rental lease A written or oral contract between a landlord and tenant that grants the tenant the right to reside at a premises for a specified period of time and under specific conditions, typically in exchange for an agreed upon periodic payment.

Renter-occupied

Fiscal year

A renter-occupied unit is a rental unit that is not vacant, but is occupied by a tenant.

This report provides data based on the North Carolina Court System’s fiscal year, which is July 1 to June 30.

Tenure

Formal eviction

Refers to whether a unit is owner-occupied or renteroccupied.

The legal process through which a landlord seeks to regain possession of a leased premises by concluding a tenant’s right to occupy the premises.

Forced move A move that is involuntary and may be due to a formal eviction, informal eviction, property foreclosure, property condemnation, or other reason that is not within the tenant’s choosing.

Hold over When a tenant stays in the premises or unit after the lease terminates.

VCAP The online civil case processing system for the North Carolina Court System, which provides data on summary ejectment case filings and results.

Writ of possession for real property A form completed by a landlord to remove a tenant from a premises 10 days after a judgment has been granted in favor of the landlord. The form is submitted to the Clerk of Court who provides it to the Mecklenburg County Sheriff’s Office to implement. The Sheriff’s Office will allow the landlord to padlock and secure the premises.

Key Definitions | 7

Introduction Evictions play an important role at the intersection of housing stability, housing instability and homelessness. Every year in Mecklenburg County, there are over 20,000 households at risk of formal eviction through the court system. Inspired by Matthew Desmond’s book Evicted: Poverty and Profit in the American City and the need to better understand the issue of evictions locally, the Housing Advisory Board of Charlotte-Mecklenburg chose to focus a series of reports on evictions in Mecklenburg County, North Carolina. Evictions in Charlotte-Mecklenburg Part 2: Mapping Evictions is the second report in this series. This is the first time eviction data have been mapped in Charlotte-Mecklenburg at the neighborhood level. While evictions take place throughout Mecklenburg County, they are concentrated in certain communities and neighborhoods. Part 2: Mapping Evictions maps two points in the eviction process: 1) the location of households who receive a complaint in summary ejectment, which means they are at risk of eviction and 2) where writs of possession to evict tenants were served. These two points in the formal eviction process are captured in data from the Mecklenburg County Sheriff’s Office. While not all households at risk for formal eviction are ultimately evicted, it is an important indicator of housing instability. When the writ is issued, it is an indicator that a household might not have the ability to move or find new housing (the household has not filed an appeal or moved within 10 days of receiving the judgement from the magistrate that they are have been formally evicted). Cluster analysis is used to identify neighborhoods with high concentrations of complaints in summary ejectment and writs of possession that were served. Neighborhood level data from the Quality of Life Explorer are incorporated to provide community context. While formal evictions are important to understand, they are an underrepresentation of all tenants who experience an eviction.

Diagram 1. Overview of eviction report series

Charlotte-Mecklenburg

8 | Introduction

01

02

03

An Introduction to Evictions

Mapping Evictions

One-month Snapshot of Eviction Court Records

Part 1 provides an overview of the impact of evictions, the eviction process in Mecklenburg County and county level data.

Part 2 maps the locations of households who received a notice of complaint in summary ejectment or a writ of possession.

Part 3 provides an in-depth look into a one-month snapshot of eviction court records from Mecklenburg County.

The report series can be accessed on the Charlotte-Mecklenburg Housing and Homelessness Dashboard http://MecklenburgHousingData.org

Key Findings

Key Findings

From FY2003 to FY2015, the number of areas where evictions concentrated increased and gradually shifted outward toward the edges of the county.

The highest rates of households at risk of formal eviction and writs of possession are found in North, East, and West Charlotte, extending to the edges of the county. The neighborhood indicators associated with higher rates of households at risk of formal eviction were: Black/African-American population, population under 18, public nutrition assistance, and neighborhood residential renovations. The indicators associated with lower rates of households at risk of formal eviction were development-based subsidized housing and single-family housing.

The neighborhoods that have been and continue to be most affected by formal evictions are located in East, Northeast, West, and Southwest Charlotte.

Neighborhoods with high rates of households at risk of formal eviction and writs of possession served tend to cluster near other neighborhoods with high rates. In clusters of neighborhoods with high rates of households at risk of formal eviction, the average rate of households at risk of formal eviction is more than double the county rate and the average rate of writs of possession served are almost three times the county average.

Households at risk of formal eviction in FY2015 Density FY2015

Rate FY2015

Key Findings | 9

Defining evictions An eviction is an action taken by a landlord to force a tenant with a written or oral lease to move from the premises where they reside. Evictions can be both formal and informal. Formal evictions are a legal process through which landlords1 attempt to regain possession of the premises from a tenant. Informal evictions do not take place through the court system and refer to landlord-initiated forced moves,i such as when a landlord tells the tenant they must leave or pays the tenant to move. Tenants may also be forced to move if the landlord defaults on their mortgage, increases rents substantially, or defers maintenance on the unit.ii One study estimates that informal evictions in Milwaukee2 comprised 48% of all forced moves (formal and informal).iii Other reasons for forced moves may include the property going into foreclosure, the property being condemned, or being demolished for redevelopment.iv

Legal reasons a landlord can evict a tenant With regard to formal evictions, there are four reasons3 listed on the North Carolina Complaint in Summary Ejectment form4 for why a landlord can attempt to evict a tenant with whom they have an oral or written lease: The defendant (tenant) failed to pay the rent due by a specific date and the plaintiff (landlord) made demand for the rent and waited the 10-day grace period before filing the complaint. In this case, the landlord must prove all three conditions (prove failure to pay rent, prove that they made a demand for rent, and prove that the demand was made 10 days before filing the complaint). The lease period ended on a specific date and the defendant is holding over after the end of the lease period. This reason is frequently selected by landlords with week-to-week or month-to month-leases in situations where the tenant is remaining on the premises after the lease expired. In this case, the landlord must prove that proper notice was given to the tenant that the lease ended. Landlords however, may include language in leases that significantly reduce the time period required for notifying a tenant.

EVICTION When a tenant with a written or oral lease is forced to move from the premises where they reside

Formal Legal process in which a landlord seeks to regain possession of a leased premises by concluding a tenant’s right to occupy the premises

Informal Tenant is forced to move from their premises through methods other than the legal process

The defendant breached the condition of the lease for which re-entry is specified. This reason is most frequently selected by landlords with written leases in cases where there is nonpayment of rent or another reason that violates the lease. Criminal activity or other activity has occurred in violation of G.S. §42-63. This action can be taken if the tenant is current on rental payments but there has been criminal activity or another activity that violates G.S. 42-63. Under this provision, it is possible to evict a specific person or the entire household.

The term “landlord” is sometimes referred to as the “provider” or “property owner.” For consistency, this report will use the term “landlord.” 2 No data on informal evictions are available for Mecklenburg County. At the time of this study, Milwaukee was the only known place where informal evictions were studied in depth. 3 If a tenant is in federally subsidized housing, there may be additional procedural rights entitled to the tenant. 4 The “Complaint in Summary Ejectment” form is the legal document the landlord completes to attempt to evict the tenant. 1

10 | Defining evictions

Data The Mecklenburg County Sheriff’s Office (Sheriff’s Office) is involved at two points in the formal eviction process, which are highlighted in blue in Diagram 3. Point 1. Tenant notified of complaint. The first point in the formal eviction process that involves the Sherriff’s Office is when the tenant is notified that they are at risk of eviction (a complaint in summary ejectment is filed against them). When a landlord submits a complaint in summary ejectment to evict the tenant, the Sheriff’s Office initially serves the tenant with the complaint by first class mail, then makes a physical attempt to serve the complaint in person or by posting the property. Point 2. Writ of possession. The second point in the formal eviction process is when the court issues a writ of possession. The Sheriff’s Office receives the writ of possession from the court and is responsible for serving the writ. When a writ is served, the Sheriff’s Office oversees the landlord padlock the unit and remove the tenant. The writ of possession data are important because they reflect tenants who did not move out on their own during the 10 day waiting period or file an appeal. These families may not have moved because they lacked the means to do so or were unable to find another affordable and decent unit. Not all writs of possession are executed. The writ may be returned at the request of the plaintiff because the tenant paid rent, they came to an agreement, the tenant moved, or the tenant received social services support to stay in their home. For this report, writs of possession were limited to only those that were successfully served by the Sheriff’s Office. Any writs that were returned or had an invalid address were not included.5 The Sheriff’s Office provided address-level data for all notices of complaint in summary ejectment and writs of possession from FY2002 to FY2015. Addresses from these data were cleaned, geocoded and mapped using the ESRI ArcMap 10.4 Geographic Information System. The data includes both single-family and multifamily units. Due to the data format, single-family and multi-family units could not be distinguished from one another. Future analyses could include linking these data to parcel-level data to examine summary ejectments and writs of possession at individual properties. It is important to note that the Sheriff’s Office does not make any decisions regarding eviction cases; it is responsible only for administering what is required by the court.

Diagram 2. Overview of data analysis process

Obtain data

Clean

Map

Analyze

Coordinated with the Sheriff’s Office to obtain data related to evictions

Research team cleaned data and limited the writs of possession to only those that were served

Address data were geocoded and mapped using GIS

Linked with Quality of Life Explorer data to analyze data across neighborhoods

5 From

FY2003 to FY2015 the Sheriff’s Office served 60% of all writs received. The remaining writs were not served due to reasons such as the writ being returned at the request of the plaintiff or Clerk’s office and incorrect or incomplete addresses.

Data | 11

Diagram 3. Eviction Process in Mecklenburg County Colored circles reflect steps in eviction process that involve the Sheriff’s Office

! Lease agreement Oral or written agreement

Issue Rent not paid or other lease violation such as tenant breaks law or does not leave after lease ends

Tenant is forced to move Tenant told they must leave, tenant paid to move, property goes into foreclosure, property is sold, or property is not maintained. This is a forced move.

1 Tenant served with a summons

Landlord files complaint in summary ejectment form

Tenant is notified of complaint and served with magistrate summons to appear for hearing

Tenant leaves to avoid formal eviction This is an informal eviction

Landlord and tenant come to an agreement Eviction avoided (dismissal)

Landlord proves case Judgment for landlord to be put in possession of premises Landlord and tenant come to an agreement Eviction avoided

Tenant or representative appears and proves case Eviction avoided

Small claims court hearing Both sides have opportunity to argue their case. Many tenants do not appear in court and do not have legal representation. Most landlords have legal representation.

Tenant moves out within 10 days Evicted Tenant does not appeal or move within 10 days

Tenant files an appeal within 10 days If tenant appeals they must pay the court fee in advance as well as their rent Eviction temporarily avoided

12 | Data

Writ of possession Landlord files a writ of possession to remove tenant from premises

Tenant moves Evicted

2 Sheriff executes writ

Landlord and tenant come to an agreement Eviction avoided

and tenant is required to leave Sheriff receives writ of possession and notifies tenant of when they plan to padlock the property. Sheriff goes with landlord to padlock the premises. The tenant is required to leave. Evicted

Tenant retrieves personal property Tenant has 5 to 7 days to retrieve personal property. Tenant may not be able to pay to have large items removed or afford a storage unit.

Findings The findings from the eviction data analysis are organized in the following sections: 1.

Eviction density. Where in Mecklenburg County are the largest concentrations of complaints in summary ejectment and writs of possession served and how has this changed over time?

2.

Eviction rates and clustering. Which neighborhoods have the highest rates of complaints in summary ejectment and writs of possession served when we account for underlying housing density? Are these neighborhoods clustered?

3.

Neighborhood characteristics. What are the characteristics of the neighborhoods with high or low rates of complaints in summary ejectment or writs of possession served?

4.

Eviction Density From FY2003 to FY2015, the number of areas where evictions concentrated increased and gradually shifted outward toward the edges of the county. The neighborhoods that have historically and continue to be most affected by formal evictions are located in East, Northeast, West, and Southwest Charlotte. The following series of maps show how the density of complaints in summary ejectment notifications and writs of possession served varies across the county and how these patterns have changed over time.6 These maps pinpoint where, regardless of neighborhood boundaries, a large number of evictions have taken place. Darker areas indicate places where there were more complaints in summary ejectment or writs of possession. Maps from three points in time are included in Figure 1 and Figure 2: FY2003 (before the Great Recession), FY2009 (during the Great Recession), and FY2015 (after the end of the Great Recession).7 From FY2003 to FY2015 the number of complaints in summary ejectment decreased. This decrease in case filings could possibly coincide with changes in the number of informal evictions or changes in tenant screening practices, but it is not possible to know for sure. While the total volume of complaints in summary ejectment and writs of possession served varied over time, the maps reveal largely similar patterns. In FY2003, one area in East Charlotte (near the intersection of W.T. Harris Boulevard and Albemarle Road) stands out as having the highest density of both complaints in summary ejectments and writs of possession served. Other areas with relatively high densities were located primarily in other parts of East, West, and to a lesser extent, Southwest and Northeast Charlotte. In FY2009, the Eastside cluster still had the highest density of evictions, but it was not as pronounced as before. At the same time, the concentration of evictions became more pronounced in some of the other areas that already had relatively high density of complaints in summary ejectments and especially writs of possession served, such as Northeast and Southwest Charlotte. In 2015, the number and extent of areas with high concentrations of evictions continued to grow and expand further out into the Northeast and Southeast edges of the county. To some degree, this outward shift in evictions reflects the continued suburbanization and expansion of overall development in the periphery of the county as well as the suburbanization of poverty. At the same time, many areas appeared to have high or relatively high concentrations of evictions across all three time periods, indicating that evictions are an enduring problem in these neighborhoods.

6 Addresses

were first mapped as dots, then smoothed into 2 mile diameter ‘neighborhoods’ to help display the underlying density of evictions. 7 For maps from additional years, please refer to the Appendix.

Findings | 13

Figure 1: Density of Complaint in Summary Ejectment notifications FY2003 to FY2015 Note: The scale of each density map is based on the total number of complaints in summary ejectment for that year. If an area gets darker over time, it does not necessarily mean that the total number of complaints in that area increased. Rather, it indicates that the number of complaints in that area increased relative to other areas of the county that year.

FY2003

FY2009

FY2015 N=39,014

N=38,613

Density

N=31,719 14 | Findings

Figure 2: Density of Writs of Possession served, FY2003 to FY2015 Note: The scale of each density map is based on the total number of writs for that year. If an area gets darker over time, it does not necessarily mean that the total number of writs in that area increased. Rather, it indicates that the number of writs in that area increased relative to other areas of the county that year.

FY2003

FY2009

FY2015 N=5,672

N=7,392

Density

N=6,694 Findings | 15

Eviction rates and neighborhood clustering The highest rates of complaints in summary ejectment and writs of possession per 100 renter units are found in North, East, and West Charlotte, extending to the edges of the county. Neighborhoods with high rates of complaints in summary ejectment and writs of possession served tend to cluster near other neighborhoods with high rates. In clusters of neighborhoods with high rates of complaints in summary ejectment, the average rate of complaints in summary ejectment is more than double the county rate and the average rate of writs of possession are almost three times the county average.

Rates Mapping eviction density helps to show where concentrations of complaints in summary ejectment and writs of possession are taking place. However, each neighborhood has a different amount of rental units, which can in turn impact the number of evictions. We account for the underlying density of rental units by also mapping the rate of complaints in summary ejectments and writs of possession served per 100 renter households.8 Mapping this rate enables the examination of which neighborhoods might have especially high eviction rates, regardless of the underlying rental supply.9 Figure 3 shows the rate of complaints in summary ejectment and writs of possession that were served per 100 renter households in FY2015. While rates vary among neighborhoods, both maps show a similar pattern. Higher rates are found in North, East, and West Charlotte, extending to the edge of the county. These areas with higher rates have a larger share of renter households and are more racially and economically diverse than the areas with the lowest rates. The lowest rates are in the South Charlotte ‘wedge’ that extends south from Uptown to Ballantyne and is bordered by Independence Boulevard and South Boulevard, and in the suburbs in North and Southeast Mecklenburg.10 When examined together in Chart 1, it appears that neighborhoods with more complaints in summary ejectment tend to have more writs of possession served (there is a positive correlation). However, there is variation as the rate of complaints in summary ejectment increases and more outliers begin to emerge. There are a few neighborhoods with similar rates of summary ejectment but fairly different rates of writs of possession (for example neighborhoods 83 and 290, and neighborhoods 183 and 316). These areas warrant further investigation as to why there are differences in the rates of writs of possession served, yet similar rates of complaints in summary ejectment.

Neighborhood clusters In addition to visualizing the patterns of eviction rates on the map, we ran a statistical test (Global Moran’s i) to confirm whether neighborhoods with high or low rates of complaints in summary ejectment and writs of possession were in fact as clustered as they appear. This analysis revealed that the patterns on the maps are not random and that neighborhoods with high rates of summary ejectments and writs of possession are indeed clustered near other neighborhoods with high rates.11 Further, we used a related statistical test to identify several types of neighborhood clusters. If the summary ejectment or writ of possession rate in the neighborhood was significantly lower than the rates around it, the neighborhood is considered a Low-High Outlier. Similarly, a neighborhood with a higher value than its 8 The

number of evictions per Neighborhood Profile Area (NPA or neighborhood) was divided by the number of renter households to get a neighborhood rate of summary ejectments and writ of possessions. NPA’s with fewer than 20 renter households were excluded due to excess variation in rates. The number of renter households was calculated using data from the Quality of Life Explorer and 2015 American Community Survey 5-year estimates. For more information on NPAs and the Quality of Life Explorer see http://mcmap.org/qol. For a neighborhood reference map, see the Appendix. 9 Rates

of summary ejectment range from zero to 150% (which can happen when households are served more than once in a Fiscal Year), while rates of Writs of Possession range from 0 to 60%. Darker areas indicate higher rates. 10 For demographic information on these areas, please refer to mcmap.org/qol. Demographic information for clusters of neighborhoods with high rates of summary ejectments and writs of possession are detailed in Table 1 and Table 2. 11 A local Moran’s i test was used to evaluate the statistical significance of each neighborhood rate in relation to the 8 closest neighborhoods around it.

16 | Findings

neighbors is a High-Low outlier. If a neighborhood and its neighbors are all significantly higher or lower than the surrounding neighborhoods, they are part of a high-high or low-low cluster respectively. The high-high clusters indicate which neighborhoods have especially high rates of summary ejectments and writs of possession. As the chart shows, there were very few high-low or low-high areas, but multiple, large high-high clusters.

Neighborhood Cluster Key High-High cluster. A neighborhood and its neighbors are all significantly higher than the surrounding neighborhoods.

High-Low outlier. A neighborhood has significantly higher rates than the surrounding neighborhoods.

Low-Low cluster. A neighborhood and its neighbors are all significantly lower than the surrounding neighborhoods.

Low-High outlier. A neighborhood has significantly lower rates than the surrounding neighborhoods.

Findings | 17

Figure 3: Summary ejectments and writs of possession served per 100 renter households For larger versions of these maps, see the Appendix. Complaint in Summary Ejectments, FY2015

Writs of Possession Served, FY2015

68

Chart 1. Relationship between summary ejectments and writs of possession served, FY2015 There is a positive correlation between the rate of complaints in summary ejectment and writs of possession served, however as the summary ejectment rate increases, the variation and outliers increases as well.

Writs of Posession Served (per 100 renter units)

30 25

83

20 292 326 229 330 346 199 234 290

15 10

183

Neighborhood ID from the Quality of Life Explorer http://mcmap.org/qol

316

5 0 0

10

20

30

40

50

60

Complaints in Summary Ejectment (per 100 renter units)

18 | Findings

70

80

Figure 4: Clusters of Summary Ejectments, FY2015

Findings | 19

Figure 5: Clusters of Writs of Possession, FY2015

20 | Findings

Tables 1 and 2 show the differences in the high-high clusters’ characteristics.12 These differences across the high-high clusters are especially notable among the writs of possession served clusters. The average rate of complaints in summary ejectment in these clusters are more than double the county rate, and the average rate of writs of possession served in these clusters are almost three times the county average. All neighborhood clusters, except those near the airport, have a higher percentage of Black/African-American residents than the overall county. In addition, some clusters have sizable Latinx populations. Some neighborhood clusters, particularly those close to Uptown have households with incomes that are half of the county average and homeownership rates that are 20% lower than the county average. A few, however, have households with higher than or near average incomes and high rates of homeownership compared to the County, but still have high rates of complaints in summary ejectment. With the exception of the ‘Airport cluster’, all clusters had rates of 311 requests that were higher than the county average, some considerably so. This was regardless of housing and nuisance code violations rates. 311 calls are requests citizens make directly with city/county government regarding service requests, bill payments, questions, comments and concerns.

Table 1. Summary Ejectment High-High Cluster Characteristics East Cluster # of Neighborhoods

West Cluster

South Cluster

County

28

23

2

425

Population

52,685

44,506

7,647

1,040,136

Rental housing units

18,702

17,381

2,651

427,109

40

39.12

41

16.55

30%

27%

31%

25%

% Black/African-American

49.9%

74.9%

33.5%

30.2%

% Latinx

28.2%

8.1%

33.8%

12.2%

$35,570

$30,040

$41,994

$56,584

25.6

48.4

31.5

23.2

39

41

46

57

$811

$939

1

1

16.7

7.3

Average summary ejectment rate* % Under 18 years old

Median household income 311 requests per 100 people Homeownership rate Median gross rent

$790 $742 Housing code violations per 100 2 4 rental units Nuisance violations per 100 rental 9.1 21.6 units *Average eviction rate among neighborhoods in cluster. Not population weighted.

12

Neighborhood level data, and data on clusters of neighborhoods can mask important variations that exists within neighborhoods. It is possible that there are some clusters that have a lot of variation and diversity in terms of housing stock and income.

Findings | 21

Table 2. Served Writs of Possession High-High Cluster Characteristics Cluster

Northeast (I-85, WT Harris)

# of Neighborhoods Population

Southeast (WT Harris,

Airport

Albemarle, 485)

West

Near Northwest

Far Northwest

North

(Wilkinson and West)

(I-85, Brookshire, Freedom,77)

(along 485, Freedom)

(Between Brookshire, I-77)

County

12

12

1

9

9

4

4

425

24,331

28,158

852

12,438

16,897

9,524

14,066

1,040,136

Rental housing units

8,667

10,391

295

6,339

6,829

3,614

4,924

42,7109

Average writs of possession served rate

10.54

10.21

24

9.58

10.16

10.39

11.18

3.77

33%

28%

32%

29%

28%

27%

22%

25%

50.8%

46.3%

7.6%

79.3%

76.6%

44.5%

69.1%

30.2%

33%

23.7%

37.3%

10%

5.6%

7.9%

10.4%

12.2%

$34,104

$44,236

$38,047

$26,851

$26,117

$50,007

$59,683

$56,584

29.8

27.5

4.8

41

57.5

40.8

32.1

23.2

38

56

72

32

36

77

78

57

$758

$869

$740

$716

$723

$1090

$1064

$939

3

1

3

4

5

2

1

1

13.6 7.7 0 *Average eviction rate among neighborhoods in cluster. Not population weighted.

18.5

23.7

15.4

7.8

7.3

% Under 18 years old % Black/African-American % Latinx Median household income 311 requests per 100 people Homeownership rate Median gross rent Housing code violations per 100 rental units Nuisance violations per 100 rental units

22 | Findings

Neighborhood Characteristics The neighborhood indicators associated with higher rates of complaints in summary ejectment were: Black/African-American population, population under 18, public nutrition assistance, and neighborhood residential renovations. The indicators associated with lower rates of complaints in summary ejectment were development-based subsidized housing and single-family housing. A regression model can show which neighborhood characteristics may be potential predictors of complaints in summary ejectment. Multiple regression analyses were conducted to examine the relationship between the rate of complaints in notice of summary ejectment at the neighborhood level and neighborhood characteristics.13 The neighborhood characteristics examined in the model include: Population under 18 years old Population size Black/AfricanAmerican 14 Public nutrition assistance Housing density Single-family housing Rental houses

Residential foreclosures Residential renovation Housing code violations Development based housing assistance15

What does “predictor” mean? Prediction shows correlations or patterns of relationships (co-relations) among variables. If those same patterns carry into the future, we can reasonably assume we will see similar outcomes. However, 'that doesn't tell us the underlying mechanisms that created the relationships we observe. The reader should not assume that any of the predictors we note in this study caused high rates of evictions.

The model reveals six neighborhood indicators as highly significant predictors of rates of complaints in summary ejectment. The neighborhood indicators associated with higher rates of complaints in summary ejectment were: Black/African-American population, population under 18 years old, public nutrition assistance, and neighborhood residential renovations. The neighborhood indicators associated with lower rates of complaints in summary ejectment were development-based subsidized housing and single-family housing. Results from the multiple regression model are provided in Table 3. The model shows that development-based subsidized housing in a neighborhood is associated with lower rates of complaints in summary ejectment. Subsidized housing decreases housing costs for families and as a result, reduces housing cost burden and instability. These data suggest that by increasing housing affordability through subsidies, households may be at less risk for eviction.

13 In

preparation for model building, summary ejectments were standardized using the following method: the number of summary ejectments in a neighborhood was divided by the number of occupied rental units, and then multiplied by 100. The standardized number represents the percent of rental units subject to summary ejectment per neighborhood. This standardization allows for meaningful comparisons across neighborhoods by taking into account the number of rental units in a neighborhood, so that neighborhoods with high/low concentrations of rental units will not skew results. 14 The number of Latinx households was too small to include in the analysis. 15 According to the Quality of Life Explorer (https://mcmap.org/qol/#82/), this includes “properties with Low-Income Housing Tax Credits, public housing developments of the Charlotte Housing Authority, developments of the Charlotte-Mecklenburg Housing Partnership, developments with funding from the Charlotte Housing Trust Fund, developments with active Section 202 Direct Loans for housing for the elderly or handicapped, units with active Project-Based Rental Assistance Section 8 Contracts through the U.S. Department of Housing and Urban Development (HUD), and units with active HOME Rental Assistance subsidies through HUD. Note: Each assisted housing unit is counted only once, even when multiple types of housing assistance are tied to the unit. The data do not include HUD Insured loans with affordability restrictions (Federal Housing Administration) or homeownership assistance.” Data on the location of households with voucher based housing assistance were not available.

23 | Findings

Neighborhoods with a higher Black/African-American population are associated with higher rates of complaints in summary ejectment.16 Research from Milwaukee shows that women in black neighborhoods are disproportionately impacted by evictions. v While each community is unique, this model supports the finding that neighborhood composition plays a similar role in Charlotte-Mecklenburg. However, our model is not able to account for gender due to lack of data. The research in Milwaukee also found that a renter’s race and gender did not make one more likely to experience an eviction compared to others.vi One factor influencing this is neighborhood segregation. According to Desmond, “if the racial and economic composition of a landlord’s tenant base remains stable, then what fluctuates is family composition and size.” vii Figure 6 maps neighborhoods with a complaint in summary ejectment notice rate of greater than 25% (top 1/5 th of neighborhoods) with neighborhood percent black. Two other indicators significantly predict higher rates of complaints in summary ejectment: youth population and the share of the population receiving public nutrition assistance. This indicates that neighborhoods with higher concentrations of households with children and those who face food insecurity are significantly more likely to have a complaint in summary ejectment. Other studiesviii , ix have found that families with children are more likely to be evicted and evictions are more prevalent in neighborhoods with a high number of children. This model supports the finding that the share of children under age 18 in a neighborhood is a significant predictor of complaints in summary ejectment, but it is not able to account for individual-level household composition. The model also found that residential renovations are associated with lower rates of complaints in summary ejectment. This could be due to the displacement of tenants in previous years as well as changes in neighborhood demographics that can come with residential renovations. Future research could examine residential renovations and historical summary ejectment data to determine if there is a correlation. While housing code violations were not found to be a significant predictor of summary ejectment notices at the neighborhood level, it is possible that any links between evictions and code violations are more concentrated at the individual property level rather than reflected across an entire neighborhood. Table 3. Results of multiple regression model predicting neighborhood summary ejectments, 2015 Our model found that this has an impact (statistically significant) Our model found that this did not have an impact (not statistically significant) Does this have an impact?

Is it associated with a higher or lower rate?

Black/African-American (2010) Public Nutrition Assistance (2015) Population under 18 (2015) Percent Single Family Housing (2016) Residential Renovations (2015) Subsidized Housing (2015)

16 Looking

Foreclosures (2016)

N/A

Housing Violations (2015)

N/A

at the mean and standard deviations of these indicators reveal the degree to which they affect summary ejectments. For each one standard deviation increase above the mean, the effect on the outcome variable will increase based on the parameter estimate.

24 | Findings

Figure 6. Black/African-American population (2010) and neighborhoods with eviction rates greater than 25%

Findings | 25

Conclusion Charlotte-Mecklenburg Evictions Part 2: Mapping Evictions analyzes the location of households that received a complaint in summary ejectment or who were served with a writ of possession. These are two important points in the formal eviction process—where households are located who are at risk of formal eviction through the legal system and where households are located who may not have the ability to move once formally evicted. When these two points in the formal eviction process are mapped, spatial patterns are revealed that reflect Charlotte's "crescent" and "wedge," echoing other established patterns related to wealth, education, housing, and health. Neighborhood characteristics are related to eviction and these maps suggest common underlying mechanisms that need further examination. The geographic patterns observed in these maps are in part reflective of a legacy of policies and structures that either intentionally or unintentionally have had discriminatory effects and disproportionately impacted households of color and households living in poverty. These discriminatory effects inhibit opportunities for Charlotte-Mecklenburg’s community members, and must be acknowledged in order to be addressed. When accounting for certain neighborhood factors, the model shows that place-based subsidized housing is associated with a lower rate of complaints in summary ejectment. This underlies the role of subsidies in helping to stabilize household and neighborhoods, however more research is required to understand the role of voucher based subsidies that are not tied to a specific location. Looking at neighborhood level patterns provides a way to help us understand how each community is impacted by evictions. However, there is variation within these neighborhoods. Future research can examine data at the individual address level to determine what is happening within specific neighborhoods. Data tell an important part of the story. The people behind the data, who live in the communities that are experiencing evictions, can provide important context for the observed changes and challenges their communities have and continue to face.

The 3rd report in this series will will provide a one-month in-depth snapshot of data from individual level summary ejectment documents in Mecklenburg County. Charlotte-Mecklenburg

The report series can be accessed on the Charlotte-Mecklenburg Housing and Homelessness Dashboard http://MecklenburgHousingData.org

on writs of posession from the

26 | Conclusion

References Desmond, M., Gershenson, C., & Kiviat, B. (n.d.). Forced Relocation and Residential Instability among Urban Renters. Retrieved from https://scholar.harvard.edu/files/mdesmond/files/desmond.etal_.2015.forcedrelation.ssr_2.pdf i

Desmond, M., & Shollenberger, T. (2015). Forced Displacement From Rental Housing: Prevalence and Neighborhood Consequences. doi:10.1007/s13524-015-0419-9 ii

iii

Ibid.

iv

Desmond, M. (2016). Evicted: Poverty and Profit in the American City. New York City, New York: Crown Publishing Group.

Desmond, M., & Shollenberger, T. (2015). Forced Displacement From Rental Housing: Prevalence and Neighborhood Consequences. doi:10.1007/s13524-015-0419-9 v

vi

Ibid.

vii

Ibid.

Desmond, M., An, W., Winkler, R., Ferriss, T., (2013). “Evicting Children.” Social Forces 92 (1): 303-327.Retrieved from https://scholar.harvard.edu/files/mdesmond/files/social_forces-2013-desmond-303-27.pdf viii

Desmond, M., Gershenson, C., Who gets evicted? Assessing individual, neighborhood, and network factors, Social Science Research (2016), http://dx.doi.org/10.1016/j.ssresearch.2016.08.017 ix

References | 27

Appendix 29 Density maps 54 Rate maps 56 Cluster maps 59 Chart: Relationship between summary ejectments and writs of possessions served 60 Neighborhood profile area reference map 61 Logo attribution

28 | Appendix

Maps

Density of Complaint in Summary Ejectment notifications

FY2003

Appendix | 29


FY2004

30 | Appendix


FY2005

Appendix | 31


FY2006

32 | Appendix


FY2007

Appendix | 33


FY2009

34 | Appendix


FY2010

Appendix | 35


FY2011

36 | Appendix


FY2012

Appendix | 37


FY2013

38 | Appendix


FY2014

Appendix | 39


FY2015

40 | Appendix

Density of Writs of Possession Served

FY2003

Appendix | 41


FY2004

42 | Appendix


FY2005

Appendix | 43


FY2006

44 | Appendix


FY2007

Appendix | 45


FY2008

46 | Appendix


FY2009

Appendix | 47


FY2010

48 | Appendix


FY2011

Appendix | 49


FY2012

50 | Appendix


FY2013

Appendix | 51


FY2014

52 | Appendix


FY2015

Appendix | 53

Complaints in Summary Ejectments per 100 renter households

FY2015

68

54 | Appendix

Writs of Possession Served per 100 renter households

FY2015

Appendix | 55

Clusters of Complaints in Summary Ejectments

FY2015

56 | Appendix

Clusters of Writs of Possession Served

FY2015

Appendix | 57

Black/African-American population (2010) and neighborhoods with eviction rates greater than 25%

FY2015

58 | Appendix

Chart 1. Relationship between summary ejectments and writs of possession served, FY2015 There is a positive correlation between the rate of complaints in summary ejectment and writs of possession served, however as the summary ejectment rate increases, the variation and outliers increases as well. 30

25

83

Writs of Posession Served (per 100 renter units)

20 183 292

15

330

Neighborhood ID from the Quality of Life Explorer http://mcmap.org/qol

229 326 346 199 234

10

290 316

5

0

0

10

20

30

40

50

60

70

80

Complaints in Summary Ejectment (per 100 renter units) Appendix | 59

Neighborhood Profile Area Reference Map For neighborhood details, refer to http://mcmap.org/QOL

60 | Appendix

Logo Attribution

Appendix | 61